Management of livestock grazing in riparian areas is an important aspect of rangeland management. Willows (Salix spp.) are a common riparian plant serving as an ecosystem stabilizer, as well as providing important habitat, but browsing or trampling by cattle can decrease willow canopy volume. Canopy volume can be measured on the ground with hours of meticulous data collection. However, canopy volume estimates from drone-collected images could be a more efficient and objective method for measuring willow canopy volume and understanding the impact of livestock use on riparian woody vegetation. Our objective was to determine how well drone-based measurements of willow canopy volume corresponded to field measurements in a southern Idaho riparian area before and after a grazing trial. We used sets of overlapping aerial images from a DJI Phantom 4 Professional drone to construct 3-dimensional point clouds of willows. From these point clouds we estimated willow canopy volume using 2 techniques and compared those with canopy volume estimates from field measurements of 58 willows ranging in height from 0.76 m to 4.57 m. Point cloud canopy volume estimates using both techniques showed high correspondence with field-estimated volume (R² > 0.8) for both pregrazing and postgrazing. However, point cloud techniques generally underestimated canopy volume compared with the field technique. Drone-based estimates took ≈4 h per sampling event (i.e., pregrazing, postgrazing) including acquiring and processing the imagery, whereas field-based measurements took ≈10 h per sampling event. These results demonstrate drone-collected images may be an effective tool for measuring and monitoring riparian woody vegetation.

河岸地区牲畜的管理是牧场管理的重要方面。柳树（柳spp。）是一种常见的河岸植物，可作为生态系统的稳定剂，并提供重要的栖息地，但是牛的浏览或践踏会降低柳树的冠层体积。可以通过收集数小时的精心数据在地面上测量树冠体积。但是，从无人机收集的图像中估算出的树冠体积可能是测量柳树冠层体积并了解牲畜使用对河岸木本植被影响的更有效，更客观的方法。我们的目标是确定在放牧试验前后，基于无人机的柳树冠层体积测量值与爱达荷州南部河岸地区的野外测量结果之间的对应程度。我们使用来自DJI Phantom 4 Professional无人机的重叠航空影像集构建了3维柳树点云。从这些点云中，我们使用两种技术估算了柳树冠层的体积，并将其与从58个高度在0.76 m至4.57 m范围内的柳树的实地测量得出的树冠体积估计值进行了比较。使用这两种技术估算的点云雨棚体积与实地估算的体积高度对应（ 放牧前和放牧后R ² > 0.8）。但是，与现场技术相比，点云技术通常低估了冠层的体积。基于无人机的估计每个采样事件（即放牧，后放牧）（包括采集和处理图像）花费约4小时，而基于现场的测量则每个采样事件花费约10小时。这些结果表明，无人机采集的图像可能是测量和监测河岸木本植被的有效工具。